Secure identification methods and systems

Abstract

There is disclosed a method of and a system for generating a unique identifier for a subject. Biometric data related to the subject is received. Identification markers from the biometric data are extracted. The unique identifier is generated from the extracted identification markers by identifying a given domain specific feature which has a predetermined identity compared to other domain specific features. Feature values are generated based on the biometric data and stored in a user profile of the subject.

1 . A method for generating a unique identifier for a subject, the method executable by a processor of a computer system, the method comprising:
 obtaining biometric data relating to the subject;   extracting identification markers from the biometric data;   generating the unique identifier from the extracted identification markers, wherein the generating the unique identifier comprises identifying a given domain specific feature which has predetermined identity compared to other domain specific features.   
     
     
         2 . The method of  claim 1 , wherein the predetermined identity has a higher occurrence than other domain specific features. 
     
     
         3 . The method of  claim 1 , wherein the predetermined identity comprises a higher frequency event than other domain specific features. 
     
     
         4 . The method of  claim 1 , wherein the domain comprises one or more of acoustic signals, vibroacoustic signals, electromagnetic signals and optical signals. 
     
     
         5 . The method of  claim 1 , wherein the given domain specific feature is characterized based on one or more of a pitch, an amplitude, a peak, an area under the curve, a frequency, a spectral distribution, a total energy, a timbre, a timing, frequency bands, and harmonic distribution. 
     
     
         6 . The method of  claim 1 , further comprising storing the generated unique identifier in a database of the processor. 
     
     
         7 . The method of  claim 1 , wherein the generating the unique identifier occurs at a first time point, the method further comprising, at a second time point, comparing the generated identifier with a reference identifier to determine a presence of predetermined common features. 
     
     
         8 . The method of  claim 7 , wherein the second time point is later than or at the same time as the first time point. 
     
     
         9 . The method of  claim 1 , further comprising one or more of:
 determining whether to accept the biometric data based on predetermined criteria;   processing the biometric data to enhance a signal thereof;   processing the biometric data to normalize a signal thereof;   processing the biometric data to perform evolutionary structural machine learning, signal aggregation and abstraction of a signal thereof; and   comparing the biometric data to reference biometric data stored in a database.   
     
     
         10 . The method of  claim 1 , wherein the generated unique identifier is a QR code. 
     
     
         11 . The method of  claim 1 , wherein the obtaining the biometric data comprises a baseline phase and a base-line update phase, a data segment in the baseline phase being larger than a data segment in the base-line update phase. 
     
     
         12 . The method of  claim 1 , wherein the obtaining the biometric data comprises acquiring data at sampling rates of about 0.01 Hz to about 20 THz. 
     
     
         13 . The method of  claim 1 , further comprising causing the processor to send the generated unique identifier to a given device, such as by Bluetooth. 
     
     
         14 . The method of  claim 1 , further comprising adding a time stamp to the generated unique identifier. 
     
     
         15 . The method of  claim 1 , further comprising obtaining input of an event related parameter, such as attending a given show, banking with a given bank, becoming infected with a given virus, and generating a status identifier incorporating information about the unique identifier and the event. 
     
     
         16 . The method of  claim 1 , further comprising obtaining input of a physical identification parameter from a device associated with the subject. 
     
     
         17 . The method of  claim 1 , further comprising converting a bit output of the generated unique identifier according to a bit requirement of another digital identification solution which has a different requirement. 
     
     
         18 . The method of  claim 1 , further comprising obtaining input of an emotional/cognitive state of the subject, and incorporating with the generated unique identifier. 
     
     
         19 . The method of  claim 1 , further comprising use of the generated unique identifier as one or more of a health passport; security access; emotional/cognitive feedback. 
     
     
         20 . A system for generating a unique identifier for a subject, the system comprising a processor of a computer system, the processor configured to execute a method as described in any one of  claims 1 - 19 . 
     
     
         21 . The system of  claim 20 , further comprising one or more sensors for obtaining the biometric data. 
     
     
         22 . The system of  claim 20 , wherein the computer system is at least partially implemented in a mobile device, the mobile device further including a physical identification portion. 
     
     
         23 . A method comprising:
 receiving an identifier of an individual;   retrieving a profile corresponding to the individual from a database of user profiles;   recording biometric data of the individual using a sensor array, wherein the sensor array comprises a vibroacoustic sensor;   retrieving an ordered list of features;   generating, based on the biometric data, one or more feature values corresponding to highest-ranked features in the ordered list of features;   determining a user profile from the database of user profiles that matches the one or more feature values;   after determining that the user profile from the database matches the retrieved profile corresponding to the individual, outputting an indication that the individual has been authenticated.   
     
     
         24 . The method of  claim 23 , wherein receiving the identifier of the individual comprises scanning a bar code corresponding to the individual. 
     
     
         25 . The method of  claim 23 , wherein receiving the identifier of the individual comprises receiving a username of the individual. 
     
     
         26 . The method of  claim 23 , wherein receiving the identifier of the individual comprises receiving an identification number corresponding to the individual. 
     
     
         27 . The method of  claim 23 , wherein the profile corresponding to the individual comprises a plurality of feature values, and wherein the feature values are based on previously recorded measurements of the individual. 
     
     
         28 . The method of  claim 23 , wherein the ordered list of features was generated by a machine learning algorithm (MLA) trained to rank features based on their ability to discriminate between individuals. 
     
     
         29 . The method of  claim 28 , wherein features that are more likely to discriminate between individuals are assigned a higher ranking in the ordered list of features. 
     
     
         30 . The method of  claim 23 , wherein determining the user profile that matches the one or more feature values comprises iterating through the ranked list of features until a unique profile matching the biometric data of the individual is found. 
     
     
         31 . The method of  claim 23 , wherein determining the user profile that matches the one or more feature values comprises iterating through the ranked list of features until an amount of potential matches for the biometric data of the individual is less than a predetermined threshold amount. 
     
     
         32 . The method of  claim 23 , wherein the sensor array comprises one or more environmental sensors, wherein the method further comprises measuring, by the one or more environmental sensors, one or more environmental parameters, and wherein generating the one or more feature values comprises generating the one or more feature values based on the one or more environmental parameters. 
     
     
         33 . A method comprising:
 recording biometric data of an individual using a sensor array, wherein the sensor array comprises a vibroacoustic sensor;   generating, based on the biometric data, a plurality of feature values;   generating a user profile of the individual, wherein the user profile comprises the plurality of feature values;   storing the user profile in a database;   generating, by a machine learning algorithm (MLA) and based on the database, a ranked list of features wherein the features are ranked based on their likelihood to discriminate between individuals; and   storing the ranked list.   
     
     
         34 . The method of  claim 33 , further comprising:
 recording, by the sensor array, one or more environmental parameters; and   storing the one or more environmental parameters in the user profile.   
     
     
         35 . The method of  claim 34 , wherein the one or more environmental parameters comprise a measured temperature and a measured humidity. 
     
     
         36 . The method of  claim 33 , wherein the database comprises a graph. 
     
     
         37 . A system comprising:
 at least one processor, and   memory storing a plurality of executable instructions which, when executed by the at least one processor, cause the system to execute a method as described in any one of  claims 23 - 36 .